Multisample Render Target Compression for Lower Graphics Bandwidth
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current graphics processing systems face challenges in efficiently managing bandwidth-intensive multisample render targets, particularly in graphics rendering techniques like multi-sampling anti-aliasing, where storing multiple samples per pixel increases bandwidth consumption.
Innovation Solution
Implementing lossless compression techniques for multisample render targets, specifically through interleaved storage of sample data, which enhances efficiency by reducing bandwidth requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple samples per pixel are stored in traditional graphics processing systems, then anti-aliasing quality is improved, but bandwidth consumption increases
Solution Approach 1:
The patent segments the multisample data into distinct planes (e.g., even samples and odd samples stored in separate planes), allowing independent compression and processing of each plane. This segmentation enables more efficient bandwidth utilization while maintaining the quality of anti-aliasing by preserving all sample data.
Solution Approach 2:
The patent implements a nested structure where multiple sample planes are organized hierarchically, with sample data nested within plane structures that can be independently managed and compressed. This nesting allows for efficient memory hierarchy utilization and reduced bandwidth consumption during data transfer.
2Loss of energy
If lossless compression is applied to multisample render targets, then bandwidth consumption is reduced, but data processing complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where the compression and decompression operations are automatically performed by dedicated hardware units within the graphics processing system. The interleaved storage format is designed to work seamlessly with these self-service compression units, reducing the need for complex external processing while maintaining lossless compression benefits.
Solution Approach 2:
The patent changes the storage parameter from traditional packed format to interleaved format, where samples from different planes are alternately stored. This parameter change enables more efficient compression ratios while maintaining data integrity, and the format is specifically designed to work with hardware compression units to minimize processing complexity.
3Loss of energy
If interleaved storage format is used for multisample data, then bandwidth efficiency is improved, but memory access patterns become more complex
Solution Approach 1:
The patent implements dynamic memory access patterns that adapt to the interleaved storage format. The system dynamically switches between different access modes (plane-by-plane access versus sample-by-sample access) depending on the specific operation being performed, optimizing bandwidth efficiency while managing access complexity through flexible, context-dependent access strategies.
Data Source
AI summary
Described herein is a data processing system having a multisample antialiasing compressor coupled to a texture unit and shader execution array. In one embodiment, the data processing system includes a memory device to store a multisample render target, the multisample render target to store color data for a set of sample locations of each pixel in a set of pixels; and general-purpose graphics processor comprising a multisample antialiasing compressor to apply multisample antialiasing compression to color data generated for the set of sample locations of a first pixel in the set of pixels and a multisample render cache to store color data generated for the set of sample locations of the first pixel in the set of pixels, wherein color data evicted from the multisample render cache is to be stored to the multisample render target.